The Effects of the 1930s HOLC Redlining Maps

Transcription

1 The Effects of the 1930s HOLC Redlining Maps Daniel Aaronson Daniel Hartley Bhashkar Mazumder Federal Reserve Bank of Chicago Minneapolis Fed, October 26, 2017 The views expressed are those of the authors and do not necessarily represent the views of the Federal Reserve Bank of Chicago, the Board of Governors of the Federal Reserve System, or its staff.

2 Introduction Place matters for many outcomes Large literature on racial segregation Our question: What were the effects of the original HOLC redlining maps Did the maps lead to urban disinvestment and shut out Blacks from attaining wealth? Lots of debate, but little systematic and quantitative evidence We trace out the effects of the maps over the period

3 Key Findings: We find that the maps led to increased segregation, reduced home ownership, lower home values and credit scores o Effects peak around 1970 to 1980 and then wane o Boundaries drawn 80 years ago are reflected in measures of financial well-being today o Long-run effects are actually stronger and more persistent in yellow-lined areas than redlined areas.

4 Background After the Great Depression, government creates a slew of new agencies to stabilize housing markets Major shift to long-term, amortized, insured loans HOLC asked to create scientific appraisal process and residential security maps for all major cities Color coded: A B C D Key variable in grades was the demographic makeup (race/ethnicity) of neighborhoods HOLC maps likely systemized, nationalized and coordinated these practices Maps influenced private lenders and FHA

5 Data We obtained geocoded HOLC maps of 149 cities (University of Richmond Digital Scholarship Lab, mapping inequality ) Use Census data address level tract level block level Credit bureau data from

6 HOLC Risk Map for San Francisco Key: (in order of risk) A=green (least) B=blue C=yellow D=red (most) U=unclassified

7 Area Description of Tacoma Detailed housing characteristics (age, repair), prices of sales etc. This might be classed as a low yellow area if not for the presence of the number of Negroes and low class Foreign families who reside in the area. Who Reviewed the Maps

8 More Evidence that Race was Pivotal Berkeley, Area 2, C grade: Northeastern part of area, north of University, could be classed as High Yellow, but for infiltration of Orientals and gradual infiltration of Negroes form south to north. Brooklyn, Bedford-Stuyvesant, Area 8, D-grade: Colored infiltration a definitely adverse influence on neighborhood desirability although Negroes will buy properties at fair prices and usually rent rooms. Oakland, Piedmont, Area 14, B-grade: Some parts of this area would be considered only High Yellow but for the rigid restrictions existing in Piedmont as to type of new construction and also the fact that there are no Negroes or Asiatics allowed in the city limits. Richmond, VA, Area 7, C-grade: Respectable people but homes are too near negro area D2 Baltimore, Area 6, C grade: No immediate danger of negro encroachment, but there is a heavy concentration of negroes in the section adjoining. Spokane, Area 10, D-grade: The territory immediately adjacent to Liberty Park is slightly better grade but proximity to largest negro concentration of the city precludes higher grading. Warren, Area 8, C-grade: Section is "killed" by influx of negroes from D-3 to attend Francis Willard School in C-8 Youngstown, Area 3, D-grade: Evergrowing influx of negroes and low class Jewish in the westerly end.

9 Minneapolis HOLC Map We are here Description of D-11

10 How We Make Our Border Comparisons

11 1) Identify Different Grade Boundaries Example: New York City

12 2) Create Boundary Buffer Zones (1/8 mile buffer around HOLC boundaries that are over ¼ mile in length)

13 We also use statistical methods to create a control group of boundaries Impose a grid over each city and find boundaries with similar gaps Also use actual HOLC boundaries with the same grade on both sides See paper for details

14 Results on Segregation

15 Effects on Segregation (C-B) Gap in Share African American, C-B Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control

16 Effects on Segregation (C-B) Gap in Share African American, C-B Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control

17 Effects on Segregation (C-B) Gap in Share African American, C-B Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control

18 Effects on Segregation (D-C) Gap in Share African American, D-C Boundary Treated Control

19 Home Ownership Results 0.04 Gap in Home Ownership, D-C Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control 0.04 Gap in Home Ownership, C-B Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control

20 House Value Results 0.3 Gap in House Value, D-C Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control 0.3 Gap in House Value, C-B Boundary (Propensity Score, Grid CF, 1/4 mile) Treated Control

21 Effects on Modern Credit Scores

22 Why Differences in Effects Between D/C and C/B? Policy: FHA 1968, CRA 1977, successfully targeted D but not C areas. Information: HOLC grades had more bite in C than D. (perhaps lending was already more restricted in D areas pre-map) Spatial investment: D quicker to be redevelop than C D closer to central business district and thus more likely to redevelop first Building stock in D depreciated more quickly and thus more suitable for redevelopment.

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24 Effects Correlated with Upward Mobility

25 Concluding Thoughts Maps long been suspected to be a factor driving urban development but little actual evidence. We find that the maps had causal effects over subsequent decades Back of envelope: Maps account for percent of overall area gaps in share African-American and home ownership over Yellow-lining effects larger and more persistent than redlining Implications for the Fed Highlights the continued importance of the Fed s community development function, it serves as one important counterweight to this historical legacy working on issues ranging from small business creation to financial literacy Importance of regulatory function in enforcing CRA Future Work: Exploiting the city-level variation to look at mechanisms Looking at the long-run individual-level outcomes of children exposed to the HOLC maps